{"id":"W3123408436","doi":"10.1109/tuffc.2021.3055141","title":"High-Frequency Array-Based Nanobubble Nonlinear Imaging in a Phantom and <i>In Vivo</i>","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Sunnybrook Hospital; University of Toronto","funders":"Institute of Cancer Research; National Cancer Institute; Canada Research Chairs; Terry Fox Research Institute; Canada Foundation for Innovation; National Institute of Biomedical Imaging and Bioengineering; Prostate Cancer Canada; Natural Sciences and Engineering Research Council of Canada; Princess Margaret Cancer Foundation","keywords":"Imaging phantom; Materials science; Scattering; Biomedical engineering; Nonlinear system; In vivo; Optics; Medical imaging; Amplitude; Acoustics; Physics; Radiology; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007449087,0.0003985695,0.0002430731,0.0003568437,0.0002789744,0.0003588705,0.0003681484,0.0004723978,0.001924642],"category_scores_gemma":[0.0004322945,0.0002963761,0.0001910218,0.0003012631,0.0004702359,0.0005611331,0.0003274023,0.0004094527,0.0005397149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004661033,"about_ca_system_score_gemma":0.0003643974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002766733,"about_ca_topic_score_gemma":0.00343591,"domain_scores_codex":[0.9997945,0.00006113421,0.000007556641,0.00006972877,0.00004462496,0.00002250963],"domain_scores_gemma":[0.9997442,0.0001094635,0.0000449321,0.00003234045,0.0000380294,0.00003104094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001554798,0.00002698898,0.0001081604,0.00006694829,0.000003901566,0.00003632976,0.00006214302,0.0005064626,0.9962149,0.0003580872,0.000174695,0.002285861],"study_design_scores_gemma":[0.00001663936,0.0003205713,0.001373354,0.000017747,0.00001779772,0.0002106285,0.00006126945,0.009326853,0.9844782,0.0002225867,0.003934785,0.00001945904],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7543501,0.005958545,0.2200877,0.001125181,0.0001963265,0.0002565128,0.0008071192,0.0009714043,0.0162472],"genre_scores_gemma":[0.7190294,0.004341254,0.2582936,0.0003977387,0.00007839304,0.0003859366,0.0008747744,0.0003847971,0.01621413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002766733,"threshold_uncertainty_score":0.006438553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004859809671819042,"score_gpt":0.1917141425552666,"score_spread":0.1868543328834476,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}